Bibliographic record
Abstract
cuadrados y se extiende sobre territorios de Argentina, Paraguay y Bolivia.La transmisión vectorial de Trypanosoma cruzi, agente causal de la enfermedad de Chagas, continúa siendo un serio problema en esta región, la cual se ha transformado en un área prioritaria de lucha contra la transmisión vectorial del parásito.En este contexto, la diversidad de T. cruzi representa un factor de importancia epidemiológica.La identificación de los diferentes linajes y genotipos multiloci del parásito mediante marcadores moleculares, permite abordar el estudio de la compleja dinámica de transmisión de T. cruzi en la región.De los seis linajes mayores de T. cruzi (TcI-TcVI), cinco de ellos están presentes en el Gran Chaco (TcI, TcII, TcIII, TcV y TcVI).Con el propósito de conocer la diversidad intralinaje, hemos obtenido y examinado aislamientos y clones de T. cruzi provenientes de los ciclos doméstico y silvestre del Chaco argentino.Los aislamientos y clones fueron examinados mediante Multilocus Enzyme Electrophoresis, Multilocus Sequence Typing, Random Amplified Polymorphic DNA, Multilocus Microsatellite Typing y análisis de la región intergénica de miniexón.Hemos identificado los linajes TcI, TcIII, TcV y TcVI.El número de genotipos multiloci en cada linaje fue: 24 en TcI, 2 en TcIII, 4 en TcV y 8 en TcVI.En el presente trabajo se discuten las implicancias de la importante diversidad observada así como también los alcances y las limitaciones de los diferentes marcadores examinados.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".